Search arXivSearch

arXiv · 2410.06761

Dynamics of contaminant flow through porous media containing random adsorbers

Abstract

Many porous media are mixtures of inert and reactive materials, manifesting spatio-chemical heterogeneity. We study the evolution of scalar transport in a chemically heterogeneous material that mimics a green roof soil substrate, fractionally composed of inert and reactive adsorbing particles. These adsorbing particles are equivalent to biochar within a real soil substrate. The scalar transport evolution is determined using experiments and simulations calibrated from experimental data. Experiment 1 is used to determine the equilibrium capacity and adsorption rate of two biochar types when immersed in a methylene blue solution. Breakthrough curves of a packed bed of glass beads with randomly interspersed biochar are determined in experiment 2. Simulations are then run to investigate the solute transport and adsorption dynamics at the pore-scale. An analytical model is proposed to capture the behavior of the biochar adsorption capacity and the simulation results are compared with experiment 2. A pore-scale analysis showed that uniformly sized beds are superior in contaminant breakthrough reduction, which is related to the adsorptive surface area and the rate at which adsorption capacity is reached. Cases using the adsorption capacity model display a tight distribution of particle surface concentration at later simulation times, indicating maximum possible adsorption. The beds with dissimilar particle sizes create more channeling effects which reduce adsorptive particle efficiency and consequently higher breakthrough concentration profiles. Comparison between experiments and simulations show good agreement. Improved biochar performance can be achieved by maintaining particle size uniformity alongside high adsorption capacity and adsorption rates appropriate to the rainfall intensity.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Kaj Pettersson, Albin Nordlander, Angela Sasic Kalagasidis, Oskar Modin, Dario Maggiolo. 2025-08-26. Dynamics of contaminant flow through porous media containing random adsorbers. https://doi.org/10.1007/s11242-025-02150-y

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Mathematical modeling on peristaltic flow of a Prandtl fluid with effects of slip conditions and inclined magnetic field

The manuscript provides a description of a theoretical analysis of a non-Newtonian Prandtl fluid subject to peristaltic flow through an inclined asymmetric channel. We explore the effect of an inclined magnetic field on the peristaltic flow. This is relevant for applications involving fluid flow in narrow, inclined (tilted) tubes similar to blood vessels or the digestive system. The model also includes thermodynamic aspects such as heat diffusion (the Soret effect) and viscous dissipation resulting from wall-fluid slip conditions, which may help optimize medical devices such as lab-on-a-chip systems and dialysis machines. In this study, the concentration of a generic chemical, temperature, and fluid velocity are taken into account through mass, heat, and momentum balances, respectively. The solution is approximated using numerical techniques suitable for long wavelengths (low frequency) and low Reynolds numbers. The study also discusses trapping phenomena, which are crucial from a clinical point of view. The developed insights can improve the understanding of physiological flows in the gastrointestinal tract and blood vessels. By understanding how the fluid moves and how particles are trapped, these insights may contribute to the design of improved medical pumps and artificial organs. Graphical visualizations are provided for the fluid velocity profile, temperature distribution, and concentration of a generic chemical. Furthermore, the numerical results are validated through comparison with a closed-form solution from a benchmark problem.

physics.flu-dyn

Discovery of a dispersion model at high Peclet numbers

Peclet number characterises the transition from classical Taylor-Aris dispersion to convection-dominated longitudinal solute transport, with the classical model becoming inadequate at extremely high radial Peclet number $Pe_r$. We develop a novel explicit-closure one-dimensional (1-D) effective dispersion model for this high-$Pe_r$ regime by introducing two closure coefficients, $θ_u$ and $θ_d$, whose functional structures are identified using low-frequency transfer-function matching and a modified Kolmogorov-Arnold network (KAN). The resulting model captures the transition from classical Taylor-Aris dispersion at low $Pe_r$ to convection-dominated dispersion at high $Pe_r$. Analysis reveals that, in the high-$Pe_r$ regime, axial transport is redistributed between the effective convection flux and the dispersive flux, resulting in a reduced macroscopic convection velocity. Numerical validation demonstrates close agreement with the convection-diffusion model over the investigated high-$Pe_r$ conditions, while the classical Taylor-Aris model exhibits substantial deviations. Application of the proposed model to averaged flow velocity inversion further demonstrates improved velocity estimation, particularly in the high-$Pe_r$ regime. These results highlight the importance of accounting for non-classical dispersion for reliable contrast-agent-based arterial blood flow velocimetry and provide new insight into high-$Pe_r$ mass transport.

physics.flu-dyn

Optimization of fluid mixing by reinforcement learning using limit cycles of a dynamical system

We propose a method to overcome the difficulties encountered when applying reinforcement learning to fluid mixing processes. The proposed method has two main features: (i) it does not require detailed measurements of the flow state, and (ii) by effectively exploiting a stable limit cycle of a two-dimensional dynamical system (the Li'enard system), it can stably perform optimization without imposing explicit constraints on the control parameters. As an illustrative example, we optimize a process in which a fluid contained in a cylindrical vessel is mixed by periodically rotating the vessel. The resulting optimal vessel motion is physically reasonable: it reverses its direction of rotation before a solid-body rotation state is established. Furthermore, even when the fluid viscosity increases with time during the mixing process, the method can continuously adapt the control parameters to the changing viscosity.

physics.flu-dyn